Nowcasting COVID-19 incidence indicators during the Italian first outbreak.
Ontology highlight
ABSTRACT:
SUBMITTER: Alaimo Di Loro P
PROVIDER: S-EPMC8242495 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundDuring COVID-19 outbreak, oncological care has been reorganized. Patients with cancer have been reported to experience a more severe COVID-19 syndrome; moreover, there are concerns of a potential interference between immune checkpoint inhibitors (ICIs) and SARS-CoV-2 pathogenesis.Materials and methodsBetween 6 and 16 May 2020, a 22-item survey was sent to Italian physicians involved in administering ICIs. It aimed at exploring the perception about SARS-CoV-2-related risks in cancer patients receiving ICIs, and the attitudes towards their management.ResultsThe 104 respondents had a median age of 35.5 years, 58.7% were females and 71.2% worked in Northern Italy. 47.1% of respondents argued a synergism between ICIs and SARS-CoV-2 pathogenesis leading to worse outcomes, but 97.1% would not deny an ICI only for the risk of infection. During COVID-19 outbreak, to reduce hospital visits, 55.8% and 30.8% opted for the highest labelled dose of each ICI and/or, among different ICIs for the same indication, for the one with the longer interval between cycles, respectively. 53.8% of respondents suggested testing for SARS-CoV-2 every cancer patient candidate to ICIs. 71.2% declared to manage patients with onset of dyspnoea and cough as infected by SARS-CoV-2 until otherwise proven; however, 96.2% did not reduce the use of steroids to manage immune-related toxicities. The administration of ICIs in specific situations for different cancer types has not been drastically conditioned.ConclusionsThese results highlight the uncertainties around the perception of a potential interference between ICIs and COVID-19, supporting the need of focused studies on this topic.
| S-EPMC7323025 | biostudies-literature
Project description:BackgroundThe COVID-19 pandemic in Italy represents a unique threat in terms of psychological distress. This cross-sectional study aims to investigate the psychological health of Italian healthcare professionals during the COVID-19 outbreak. We assessed participants' current psychological distress and coping strategies in the midst of the COVID outbreak (March-April 2020), and also asked them to retrospectively report how they remember feeling before the COVID-19 outbreak (December 2019). We examined associations between psychological distress and coping strategies with mental health and infection perceptions.MethodsSelf-administered questionnaires were distributed online to healthcare professionals (N = 580) residing in different Italian regions from 26 March to 9 April 2020. The questionnaire measured changes in psychological states, coping strategies, and demographic variables testing variations in mental health and infection risk perception among Italian healthcare workers.ResultsOverall, approximately 33.5 per cent of healthcare professionals in our sample meet the threshold for psychiatric morbidity. Participants perceive their current psychological health to be worse during the COVID-19 emergency outbreak as compared to before the outbreak, and this was especially true among women.ConclusionsBoth immediate and long-term monitoring psychological assistance services for healthcare workers should be implemented by national institutions to re-establish the psychological well-being and enhance the self-confidence and resilience of hospital personnel.
| S-EPMC7675316 | biostudies-literature
Project description:PurposeBreast cancer (BC) patients' (pts) management was affected by a global reorganization after Coronavirus disease 2019 (COVID-19). Our multicenter study aimed to assess the impact of COVID-19 on access to diagnosis, staging and treatment for BC pts compared to pre-pandemic.MethodsMedical records of all consecutive newly diagnosed BC pts referred to 6 Italian Institutions between March and December 2020 were assessed. Monthly access rate and temporal intervals between date of symptoms onset, radiological, cytohistological diagnosis and treatment start were analyzed and compared with 2019.ResultsA reduction (25%) in newly diagnosed BC was observed compared to 2019 (666 vs 890). New BC pts in 2020 were less likely to be diagnosed with early stage BC (77% vs 83%, p < 0.01), had a worse performance status according to the Eastern Cooperative Oncology Group (ECOG PS) (19.8% had PS > 0 in 2020 vs 16.5% in 2019, p < 0.01) and fewer pts were asymptomatic at diagnosis in 2020 (54% vs 71%,p < 0.01). COVID-19 did not negatively impact in terms of access to diagnosis, staging and treatment. Time intervals between symptom onset and radiological diagnosis, symptom onset and cytohistological diagnosis, cytohistological diagnosis and treatment start were maintained or improved. However, less cases were discussed in multidisciplinary tumor meetings during 2020 (60% vs 73%, p < 0.01).ConclusionsOur data proved an alarming reduction of early stage BC associated with the COVID-19 crisis in 2020. Despite the upheaval generated by the pandemic, our study shed light on the effective performance delivered by Italian Oncology Departments to guarantee diagnostic-therapeutic pathways.
| S-EPMC9388078 | biostudies-literature
Project description:The hospitals in Japan have hitherto had complete autonomy in deciding whether to admit COVID-19 patients. In fact, they were "swinging" between admitting or not COVID-19 patients, especially during the initial COVID-19 outbreak. To address endogenous decision making, we estimated the effect of admitting COVID-19 patients on hospital profits using instrumental variable (IV) regression. We derived the IVs from the guidelines of the national government on which hospital types should admit COVID-19 patients. Our empirical results revealed that the monthly profits per bed decreased by approximately JPY 600,000 ( ≈ USD 4615), which is 15 times the average monthly profit in 2019. This overwhelming financial damage indicates it is costly for some hospitals to treat COVID-19 patients because of their low suitability in admitting such patients. Based on the implications of our main results, we propose an alternative strategy to handling patient surges in case of new infectious disease outbreaks.
| S-EPMC9334161 | biostudies-literature
Project description:England has been heavily affected by the SARS-CoV-2 pandemic, with severe 'lockdown' mitigation measures now gradually being lifted. The real-time pandemic monitoring presented here has contributed to the evidence informing this pandemic management throughout the first wave. Estimates on the 10 May showed lockdown had reduced transmission by 75%, the reproduction number falling from 2.6 to 0.61. This regionally varying impact was largest in London with a reduction of 81% (95% credible interval: 77-84%). Reproduction numbers have since then slowly increased, and on 19 June the probability of the epidemic growing was greater than 5% in two regions, South West and London. By this date, an estimated 8% of the population had been infected, with a higher proportion in London (17%). The infection-to-fatality ratio is 1.1% (0.9-1.4%) overall but 17% (14-22%) among the over-75s. This ongoing work continues to be key to quantifying any widespread resurgence, should accrued immunity and effective contact tracing be insufficient to preclude a second wave. This article is part of the theme issue 'Modelling that shaped the early COVID-19 pandemic response in the UK'.
| S-EPMC8165585 | biostudies-literature
Project description:To assess the current dynamics of an epidemic, it is central to collect information on the daily number of newly diseased cases. This is especially important in real-time surveillance, where the aim is to gain situational awareness, for example, if cases are currently increasing or decreasing. Reporting delays between disease onset and case reporting hamper our ability to understand the dynamics of an epidemic close to now when looking at the number of daily reported cases only. Nowcasting can be used to adjust daily case counts for occurred-but-not-yet-reported events. Here, we present a novel application of nowcasting to data on the current COVID-19 pandemic in Bavaria. It is based on a hierarchical Bayesian model that considers changes in the reporting delay distribution over time and associated with the weekday of reporting. Furthermore, we present a way to estimate the effective time-varying case reproduction number Re(t) based on predictions of the nowcast. The approaches are based on previously published work, that we considerably extended and adapted to the current task of nowcasting COVID-19 cases. We provide methodological details of the developed approach, illustrate results based on data of the current pandemic, and evaluate the model based on synthetic and retrospective data on COVID-19 in Bavaria. Results of our nowcasting are reported to the Bavarian health authority and published on a webpage on a daily basis (https://corona.stat.uni-muenchen.de/). Code and synthetic data for the analysis are available from https://github.com/FelixGuenther/nc_covid19_bavaria and can be used for adaption of our approach to different data.
| S-EPMC7753318 | biostudies-literature
Project description:The pandemic of 2019 coronavirus disease (COVID-19) has burdened extraordinary psychological stress on the healthcare workforce. The present survey aimed to examine the personal resources and psychological symptoms associated with burnout in 933 healthcare workers in Italy during the COVID-19 outbreak period. Sociodemographic and occupational data, depression, anxiety, burnout, and post-traumatic symptoms, as well as psychological well-being, were cross-sectional assessed through an online questionnaire. A considerable part of the sample scored over the clinical levels of depression (57.9%), anxiety (65.2%), post-traumatic symptoms (55%), and burnout (25.61%). Working in the front-line (p <.05), being part of the medical staff (p <.05), experiencing lower levels of psychological well-being (p <.001), and higher levels of post-traumatic symptoms (p <.001) independently explained 38% of burnout variance. The healthcare industry, services, and professionals should be aware of the harmful effects of COVID-19 on healthcare workers and take adequate preventive measures.
| S-EPMC8145524 | biostudies-literature
Project description:While the incidence of thrombotic complications in critically ill patients is very high, in patients under non-invasive respiratory support (NIS) is still unknown. The specific incidence of thrombotic events in each of the clinical scenarios within the broad spectrum of severity of COVID-19, is not clearly established, and this has not allowed the implementation of thromboprophylaxis or anticoagulation for routine care in COVID-19. Patients admitted in a semi-critical unit treated initially with NIS, especially Continuous-Positive Airway Pressure (CPAP), were included in the study. The cumulative incidence of pulmonary embolism was analyzed and compared between patients with good response to NIS and patients with clinical deterioration that required orotracheal intubation. 93 patients were included and 16% required mechanical ventilation (MV) after the NIS. The crude cumulative incidence of the PE was 14% (95%, CI 8-22) for all group. In patients that required orotracheal intubation and MV, the cumulative incidence was significantly higher [33% (95%, CI 16-58)] compared to patients that continued with non-invasive support [11% (CI 5-18)] (Log-Rank, p = 0.013). Patients that required mechanical ventilation were at higher risk of PE for a HR of 4.3 (95%CI 1.2-16). In conclusion, cumulative incidence of PE is remarkably higher in critically patients with a potential impact in COVID-19 evolution. In this context, patients under NIS are a very high-risk group for developing PE without a clear strategy regarding thromboprophylaxis.
| S-EPMC7857998 | biostudies-literature
Project description:Surveillance is critical to mounting an appropriate and effective response to pandemics. However, aggregated case report data suffers from reporting delays and can lead to misleading inferences. Different from aggregated case report data, line list data is a table contains individual features such as dates of symptom onset and reporting for each reported case and a good source for modeling delays. Current methods for modeling reporting delays are not particularly appropriate for line list data, which typically has missing symptom onset dates that are non-ignorable for modeling reporting delays. In this paper, we develop a Bayesian approach that dynamically integrates imputation and estimation for line list data. Specifically, this Bayesian approach can accurately estimate the epidemic curve and instantaneous reproduction numbers, even with most symptom onset dates missing. The Bayesian approach is also robust to deviations from model assumptions, such as changes in the reporting delay distribution or incorrect specification of the maximum reporting delay. We apply the Bayesian approach to COVID-19 line list data in Massachusetts and find the reproduction number estimates correspond more closely to the control measures than the estimates based on the reported curve.
| S-EPMC8297945 | biostudies-literature